IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-04273656.html
   My bibliography  Save this paper

An environmental Luenberger–Hicks–Moorsteen total factor productivity indicator: empirical analysis considering undesirable outputs either as inputs or outputs, and attention for infeasibilities

Author

Listed:
  • Zhiyang Shen

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Kristiaan Kerstens

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Tomas Baležentis

    (Vilnius University [Vilnius])

Abstract

The measurement of economic growth is important for identifying the development patterns followed by different economies. In the light of sustainable development goals, one needs to be able to track the green growth, i.e., they must the adjusted in regard to generation of undesirable outputs that are usually non-marketed. This contribution puts forward an empirical case of the economically developed countries grouped in OECD and measures their total factor productivity (TFP) growth. This is done by exploiting a novel formulation of the Luenberger–Hicks–Moorsteen (LHM) TFP indicator based on the Kuosmanen (Am J Agric Econ 87(4):1077–1082, 2005) proposal. We argue that undesirable outputs must be regarded as special outputs but not inputs in both the production technology and TFP measure. We compare two models: one that considers undesirable outputs as special outputs in the directional distance functions of TFP indicator following Kuosmanen (Am J Agric Econ 87(4):1077–1082, 2005), and another that considers undesirable outputs as inputs following Abad (J Environ Manage 161:325–334, 2015). This proposed approach assumes that input- and output-orientations are taken, with the latter handling both desirable and undesirable outputs simultaneously. Still, we compare our results with those based on the other more conventional frameworks. The empirical case deals with OECD country-level data for 1991–2019. The results suggest that there exist substantial differences in the resulting measures of the TFP growth depending on the distance functions used in the calculation of the LHM indicator.

Suggested Citation

  • Zhiyang Shen & Kristiaan Kerstens & Tomas Baležentis, 2023. "An environmental Luenberger–Hicks–Moorsteen total factor productivity indicator: empirical analysis considering undesirable outputs either as inputs or outputs, and attention for infeasibilities," Post-Print hal-04273656, HAL.
  • Handle: RePEc:hal:journl:hal-04273656
    DOI: 10.1007/s10479-023-05482-4
    Note: View the original document on HAL open archive server: https://hal.science/hal-04273656
    as

    Download full text from publisher

    File URL: https://hal.science/hal-04273656/document
    Download Restriction: no

    File URL: https://libkey.io/10.1007/s10479-023-05482-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Diewert, W. Erwin & Fox, Kevin J., 2014. "Reference technology sets, Free Disposal Hulls and productivity decompositions," Economics Letters, Elsevier, vol. 122(2), pages 238-242.
    2. Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2015. "The Next Generation of the Penn World Table," American Economic Review, American Economic Association, vol. 105(10), pages 3150-3182, October.
    3. Chen, Jiandong & Wang, Ping & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2018. "Decomposition and decoupling analysis of CO2 emissions in OECD," Applied Energy, Elsevier, vol. 231(C), pages 937-950.
    4. Po-Chi Chen & Ming-Miin Yu, 2014. "Total factor productivity growth and directions of technical change bias: evidence from 99 OECD and non-OECD countries," Annals of Operations Research, Springer, vol. 214(1), pages 143-165, March.
    5. W. Briec & K. Kerstens, 2009. "Infeasibility and Directional Distance Functions with Application to the Determinateness of the Luenberger Productivity Indicator," Journal of Optimization Theory and Applications, Springer, vol. 141(1), pages 55-73, April.
    6. repec:bla:scandj:v:98:y:1996:i:2:p:303-13 is not listed on IDEAS
    7. Ang, Frederic & Kerstens, Pieter Jan, 2020. "A superlative indicator for the Luenberger-Hicks-Moorsteen productivity indicator: Theory and application," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1161-1173.
    8. Arnaud Abad, 2015. "An environmental generalised Luenberger-Hicks-Moorsteen productivity indicator and an environmental generalised Hicks-Moorsteen productivity index," Post-Print hal-03025374, HAL.
    9. Walter Briec & Kristiaan Kerstens, 2004. "A Luenberger-Hicks-Moorsteen productivity indicator: its relation to the Hicks-Moorsteen productivity index and the Luenberger productivity indicator," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 23(4), pages 925-939, May.
    10. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    11. Robert G. Chambers, 2002. "Exact nonradial input, output, and productivity measurement," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 20(4), pages 751-765.
    12. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    13. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    14. Diewert, W. Erwin & Fox, Kevin J., 2017. "Decomposing productivity indexes into explanatory factors," European Journal of Operational Research, Elsevier, vol. 256(1), pages 275-291.
    15. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    16. Walter Briec & Kristiaan Kerstens, 2011. "The Hicks–Moorsteen Productivity Index Satisfies The Determinateness Axiom," Manchester School, University of Manchester, vol. 79(4), pages 765-775, July.
    17. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    18. Atkinson, Scott E & Cornwell, Christopher & Honerkamp, Olaf, 2003. "Measuring and Decomposing Productivity Change: Stochastic Distance Function Estimation versus Data Envelopment Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 284-294, April.
    19. Ang, Frederic & Kerstens, Pieter Jan, 2017. "Decomposing the Luenberger–Hicks–Moorsteen Total Factor Productivity indicator: An application to U.S. agriculture," European Journal of Operational Research, Elsevier, vol. 260(1), pages 359-375.
    20. Chen, Bin & Jin, Yingmei, 2020. "Adjusting productivity measures for CO2 emissions control: Evidence from the provincial thermal power sector in China," Energy Economics, Elsevier, vol. 87(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tomas Balezentis & Kristiaan Kerstens & Zhiyang Shen, 2022. "Economic and Environmental Decomposition of Luenberger-Hicks-Moorsteen Total Factor Productivity Indicator: Empirical Analysis of Chinese Textile Firms With a Focus on Reporting Infeasibilities and Qu," Post-Print hal-03833245, HAL.
    2. Tomas Balezentis & Zhiyang Shen, 2017. "An environmental Luenberger-Hicks-Moorsteen. Total Factor Productivityindicator for OECD Countries," Working Papers 2017-EQM-02, IESEG School of Management.
    3. Ang, Frederic & Kerstens, Pieter Jan, 2020. "A superlative indicator for the Luenberger-Hicks-Moorsteen productivity indicator: Theory and application," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1161-1173.
    4. Arnaud Abad & Paola Ravelojaona, 2020. "A Generalization of Environmental Productivity Analysis," Working Papers hal-02964799, HAL.
    5. Mocholi-Arce, Manuel & Sala-Garrido, Ramon & Molinos-Senante, Maria & Maziotis, Alexandros, 2021. "Water company productivity change: A disaggregated approach accounting for changes in inputs and outputs," Utilities Policy, Elsevier, vol. 70(C).
    6. Frederic Ang & Kristiaan Kerstens & Jafar Sadeghi, 2023. "Energy productivity and greenhouse gas emission intensity in Dutch dairy farms: A Hicks–Moorsteen by‐production approach under non‐convexity and convexity with equivalence results," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 492-509, June.
    7. Ang, Frederic & Kerstens, Pieter Jan, 2017. "Decomposing the Luenberger–Hicks–Moorsteen Total Factor Productivity indicator: An application to U.S. agriculture," European Journal of Operational Research, Elsevier, vol. 260(1), pages 359-375.
    8. Haiyan Deng & Ge Bai & Kristiaan Kerstens & Zhiyang Shen, 2023. "Comparing green productivity under convex and nonconvex technologies: Which is a robust approach consistent with energy structure?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(8), pages 4377-4394, December.
    9. Frederic Ang & Pieter Jan Kerstens, 2023. "Robust nonparametric analysis of dynamic profits, prices and productivity: An application to French meat-processing firms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(2), pages 771-809.
    10. Ang, Frederic & Kerstens, Pieter Jan, 2017. "The Dynamic Luenberger-Hicks-Moorsteen Productivity Indicator With An Application To Dairy Farms In South West England," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 260831, European Association of Agricultural Economists.
    11. Stefano NASINI & Rabia NESSAH, 2021. "Endogenous Learning in Multi-Sector Economies," Working Papers 2021-EQM-08, IESEG School of Management, revised Oct 2023.
    12. Frederic Ang & Stephen J. Ramsden, 2024. "Analysing determinate components of an approximated Luenberger–Hicks–Moorsteen productivity indicator: An application to German dairy‐processing firms," Agribusiness, John Wiley & Sons, Ltd., vol. 40(2), pages 349-370, April.
    13. Arnaud Abad & Paola Ravelojaona, 2022. "A generalization of environmental productivity analysis," Post-Print hal-03592375, HAL.
    14. Briec, Walter & Kerstens, Kristiaan & Prior, Diego & Van de Woestyne, Ignace, 2018. "Testing general and special Färe-Primont indices: A proposal for public and private sector synthetic indices of European regional expenditures and tourism," European Journal of Operational Research, Elsevier, vol. 271(2), pages 756-768.
    15. Kerstens, Kristiaan & Van de Woestyne, Ignace, 2014. "Comparing Malmquist and Hicks–Moorsteen productivity indices: Exploring the impact of unbalanced vs. balanced panel data," European Journal of Operational Research, Elsevier, vol. 233(3), pages 749-758.
    16. Zhiyang Shen & Vivian Valdmanis, 2022. "Assessing total factor productivity across Africa: an empirical investigation," Journal of Productivity Analysis, Springer, vol. 58(2), pages 239-253, December.
    17. Briec, Walter & Kerstens, Kristiaan, 2009. "The Luenberger productivity indicator: An economic specification leading to infeasibilities," Economic Modelling, Elsevier, vol. 26(3), pages 597-600, May.
    18. A. Abad & P. Ravelojaona, 2022. "A generalization of environmental productivity analysis," Journal of Productivity Analysis, Springer, vol. 57(1), pages 61-78, February.
    19. Briec, Walter & Dumas, Audrey & Kerstens, Kristiaan & Stenger, Agathe, 2022. "Generalised commensurability properties of efficiency measures: Implications for productivity indicators," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1481-1492.
    20. A. Abad & P. Ravelojaona, 2017. "Exponential environmental productivity index and indicators," Journal of Productivity Analysis, Springer, vol. 48(2), pages 147-166, December.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-04273656. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.